A key
tenet of the philosophy of science is that science progresses when a more
general theory is formulated. That is, an aim of science is to explain as many
phenomena as possible with as few statements as possible. This idea, that more
general theories are preferred over more specialized theories, lies at the heart
of systems science. But are there different ways in which a theory can be more
general? Is there a tradeoff between universality and testability? Does
increasing generalization lead to a loss of information and utility? An
examination of several principles from systems theory and cybernetics suggests
three conclusions: there are two types of general theories; general theories
requires "domain specific knowledge" to make the connection between theory and
experiment or between theory and practice; and theories which are more general
than those formulated in the traditional disciplines can be effective at
facilitating communication among disciplines.

1. INTRODUCTION

How
does scientific knowledge develop? Is knowledge in systems science different
from knowledge in other scientific fields? If it is different, in what way is
it different? Are the systems sciences a revolution in one or more previous
sciences, the addition of a new domain of inquiry, or a new type of inquiry
lying perhaps between mathematics and the sciences?

Karl
Popper claimed that science advances by conjectures and refutations, and he
preferred bold conjectures to more modest conjectures. [1] Indeed a goal of
science is parsimony in theories. The aim is to develop the smallest number of
propositions to explain the largest number of phenomena. But Popper also
maintained that theories should be falsifiable. Can a theory be too general?
Is there a trade-off between the universality of a theory and its testability?

Identifying more general theories is important because it points to the more
significant contributions in a field. An examination of key principles in
cybernetics and systems theory suggests that two types of theories currently
exist within the systems sciences. One type of general theory adds a new
dimension which had previously been neglected or had been assumed to be
insignificant. The second type of general theory is a more abstract version of
previous theories. The first type of contribution is consistent with the
correspondence principle, a principle in the philosophy of science which
stipulates how to construct a more general theory. The second type of
contribution does not advance a single discipline. Rather, it identifies the
common structures among theories in several disciplines. These theories can be
said to lie between mathematics and the existing sciences. Distinguishing these
two types of more general theories tells us something about the way that science
progresses and about the particular contribution of systems science.

2. THEORIES
WHICH ADD A NEW DIMENSION

The
correspondence principle can serve as a guide to the most significant
developments in a scientific field. Weidner and Sells have defined the
correspondence principle as follows: "Any new theory -- whatever its character
or details -- must reduce to the well established theory to which it corresponds
when the new theory is applied to the circumstances for which the less general
theory is known to hold. This principle was first applied to the

theory of atomic
structure by Niels Bohr in 1923." [2] The correspondence principle provides a
procedure for checking a new theory even before any experiments are made. For
instance, relativity equations reduce to Newtonian formulations when velocities
are much smaller than the speed of light. Wladislaw Krajewski has emphasized
that the correspondence principle does not apply to all examples of more general
theories, only to theories which add a new dimension. [3]

How
can the correspondence principle be applied to general systems theory? What
laws or theorems does it identify as being major contributions to the field?
Two examples are provided below.

2.1. The
Thermodynamics of Open Systems

Explaining the thermodynamics of living systems has been a concern of systems
theorists since the early days of the field. Von Bertalanffy argued against the
vitalists's notion that living systems violate the second law of thermodynamics.
[4] The heat death of the Universe was a subject dealt with by Norbert Wiener.
[5] Ilya Prigogine and his colleagues have extended the work on the
thermodynamics of open systems.

The
main point is that the Clausius-Carnot inequality governing the variation of
entropy during a time interval dt takes the form

dS =
deS + diS diS > 0

where
deS is the flow of entropy due to exchanges with the surroundings and diS is the
entropy production due to irreversible processes inside the system such as
diffusion, chemical reactions, heat conduction, and so on. For an isolated
system deS is zero, and

dS =
deS + diS reduces to dS = diS > 0. [6]

In
Prigogine's theory a closed system is a special case of an open system. In
accord with the correspondence principle, a new dimension, deS, the flow of
entropy through the system, has been added.

2.2. Second
Order Cybernetics

In the
case of second order cybernetics a new dimension has been added not just to a
specific scientific field but to the scientific process itself. The new
dimension is "the amount of attention paid to the observer." The previous
conception of science was that observations were or should be independent of the
characteristics of the observer. In recent years, however, a number of quite
different disciplines have been converging on the idea that neglecting the role
of the observer is no longer tenable. [7] In accord with the correspondence
principle the new formulation reduces to the old formulation when the
characteristics of the observer are disregarded. [8]

3. MORE ABSTRACT
THEORIES

The
second type of general theory in the systems sciences are theories which are
more abstract than theories in the more specialized disciplines. These theories
do not follow the correspondence principle. They do not define a new
dimension. Rather, these theories identify the common features or structures of
several more specific theories. They are not interdisciplinary theories but
rather metadisciplinary theories. The primary contributor of theories of this
kind to cybernetics and systems science was Ross Ashby. Ashby presented the
case for a scientific approach to general systems theory as follows.

The
method of considering all possible systems, regardless of whether they actually
exist in the real world, has already been used, and shown its value, in many
well established sciences...Much of its (physics) theory is concerned with
objects that do not exist and never have existed: particles with mass but no
volume, pulleys with no friction, springs with no mass, and so on. But to say
that these entities do not exist does not mean that mathematical physics is mere
fantasy. The mass-less spring, though it does not exist in the real world, is a
most important concept; and a physicist who understands its theory is better
equipped to deal with, say, the balance of a watch than one who has not mastered
the theory.

I
would suggest that a similar logical framework would be desirable as a part of
general systems theory. The forms occurring in the real world are seldom an
orderly or a complete set. If they are to be related to one another, and higher
relations and laws investigated, a rigorous logic of systems must be developed,
forming a structure on which all the real forms may find their natural places
and their natural relations. [9]

3.1 The Law of
Requisite Variety

The
law of requisite variety was proposed by Ashby at least as early as 1952. There
are basically two interpretations of it. 1) The amount of appropriate selection
that can be performed is limited by the amount of information available. 2) For
appropriate regulation the variety in the regulator must be equal to or greater
than the variety in the system being regulated. Or, the greater the variety
within a system, the greater its ability to reduce variety in its environment
through regulation.

Shannon's tenth theorem relating to the suppression of noise is a special case
of the law of requisite variety. Shannon's theorem states that the capacity of
a correction channel places a limit on the amount of correction that may be made
in a noisy channel. [10] Ashby's law is more general because it applies in all
cases involving selection based on information, not simply in the case of a
correction channel for a communication system.

The
law of requisite variety has far-reaching implications in the practical world.
The law suggests a way to calculate the appropriate size of a regulator, once
the amount of variety that the regulator is to control has been specified. The
regulator in question may be a computer, a person, a corporation or a federal
agency. The law also suggests strategies for improving the effectiveness of
regulation -- one can either reduce the variety in the system being regulated or
increase the size of the regulator. [12] Although many disciplines assume the
importance of communication and decision-making, the law of requisite variety
proposes a quantitative relationship between the two.

3.2. A Theory of
Adaptive Behavior

In
1952 Ross Ashby published Design for a Brain: The Origin of Adaptive Behavior.
[11] His idea was that every adaptive mechanism (including organisms and
organizations) must do two things -- handle day to day problems and periodically
restructure itself. In the case of a manufacturing organization it must both
produce the current product and periodically develop a new product or reorganize
itself. An organization which can both successfully produce an existing product
and develop a series of new products is likely to be adaptive. This theory
provides a theoretical foundation for the various fields of management whether
in business, government, education, health care, etc. It also provides a
theoretical foundation for social and organizational learning.

3.3.
Self-organizing Systems

The
idea of self-organization was stated succinctly by Ashby. "Every isolated
determinant dynamic system obeying unchanging laws will develop 'organisms' that
are adapted to their 'environments'." He explains the theorem as follows:

The
argument is simple enough in principle. We start with the fact that systems in
general go to equilibrium. Now most of a system's states are non-equilibrial
(if we exclude the extreme case of a system in neutral equilibrium). So in
going from any state to one of the equilibria, the system is going from a larger
number of states to a smaller. In this way it is performing a selection, in the
purely objective sense that is rejects some states, by leaving them, and retains
some other state, by sticking to it. Thus, as every determinate system goes to
equilibrium, so does it select. We have heard AD NAUSEAM the dictum that a
machine cannot select; the truth is just the opposite: every machine, as it
goes to equilibrium, performs the corresponding act of selection. [13]

It is
important to note that the system that is organizing itself is a closed system.
Both organisms and environments are present within "the system." If the
original system is not very complex, the "organisms" and "environments" that
evolve will be simple and uninteresting. However, if the original system
contains considerable variety, for example, a community or an ecosystem, the
organisms and environments that evolve can be quite complex.

Basically two processes are involved in self-organization -- the creation of new
entities and the selection of appropriate entities. Ashby tended to emphasize
the very general nature of selection whereas Von Foerster emphasized the
creation of new entities. [14]

The
principle of self-organization constitutes a more general theory that
encompasses Darwin's theory of natural selection, learning theory, and theories
of political and economic development. In Darwin's theory the environment
determines which species are best able to survive in a particular ecological
niche. "The dead shall not breed." In learning theory the environment --
whether parents, school or culture -- rewards appropriate behavior and does not
reward inappropriate behavior. In politics candidates that appeal to the
largest number of voters are elected. In market economies companies that
produce a consistently high return on investment are the most likely to
survive.

4. THE NEED FOR
DOMAIN SPECIFIC KNOWLEDGE

How
scientific progress requires not only more general theories but also testable
theories. The demand that theories be useful is one way of obtaining
falsifiability. Theories which add a new dimension require that new procedures
be developed. New procedures which lead to new or improved results lend
empirical weight to a theory and provide instances of the failure of
falsification.

In the
case of more abstract theories, there is a need for "domain specific knowledge"
to operationalize the more general theory. More abstract theories are very
helpful in identifying the similarities among theories in two or more fields,
but simply knowing the abstract theory is not sufficient. If one wants to apply
cybernetics to the design of computers, one must know electrical engineering.
And if one wants to apply cybernetics to the management of a business firm, one
must know a lot about business and finance. Hence, for people interested only
in one particular domain, a more general theory may not seem to be very useful.
This remoteness of abstract theories from the domain of application and the
existence of more readily applicable descriptions, helps to explain why systems
science has not more rapidly become institutionalized on university campuses.

5. AN
IMPLICATION FOR THE STRUCTURE OF UNIVERSITIES

The
correspondence principle is a fairly well-known idea in the philosophy of
science. It defines a way of making an important contribution to a specific
field of science, or, in the case of second order cybernetics, to all of
science. However, the second type of general theory has received less attention
in the philosophy of science. Perhaps the principal contributor of these
theories has been the systems science community.

There
is an important implication of this second type of general theory. The original
purpose of general systems theory was to help people in different disciplines
learn from one another. Kenneth Boulding described the intention in this way.

We had
no illusions that we could find the general

theory
of practically everything. We all respected

the
disciplines and the discipline that went with

them.
We also were disturbed about their isolation

and
anxious to induce a little intellectual voyeurism

into
the intellectual community, to encourage people

to
look into other people's disciplines, even if only

through the window. One of my own interests at the

time
was the hope that out of this might come economies

in
teaching. The students met many of the same

concepts, often under different names in different

disciplines, where they had to learn them all over

again,
and I hoped that if we could find structures of

theory
which were common to a number of different

disciplines, this would make it easier for the

disciplines to be learned and to interact. [15]

Has
systems science achieved this purpose? If it has, there are important
implications for the structure of universities. That is, if systems science
contributes to the productivity of the more specialized disciplines, or
facilitates communication among people in different disciplines, then education
and research on a university campus would seem to be enhanced by having a
systems science program.